Daniel Nagaj

1.3k citations
28 papers · 765 · h-index 18

Impact in

Papers in

Daniel Nagaj

28 papers receiving 738 citations

Peers

Daniel Nagaj
Comparison fields: 5 of 44
  • Artificial Intelligence 603
  • Atomic and Molecular Physics, and Optics 466
  • Computational Mathematics 9
  • Computational Theory and Mathematics 139
  • Condensed Matter Physics 74
Replace M. Van den Nest with:
M. Van den Nest Austria
A. Shen United States
M. Vyalyi United States
A. Kitaev United States
K. G. H. Vollbrecht Germany
Johannes Bausch United Kingdom
Sevag Gharibian United States
A. Torres United States
Anthony Nguyen United States
Bill Fefferman United States
Daniel Nagaj relative to M. Van den Nest Austria M. Van den Nest's profile →
Citations per field
00.5×2×3×
M. Van den Nest · 1×
Citations per year

Countries citing papers authored by Daniel Nagaj

Since Specialization
Citations

This map shows the geographic impact of Daniel Nagaj's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel Nagaj with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Nagaj more than expected).

Fields of papers citing papers by Daniel Nagaj

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Nagaj. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel Nagaj. The network helps show where Daniel Nagaj may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniel Nagaj, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Nagaj Line = papers co-authored together Daniel Nagaj links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012110
2 201269
3 202058
4 200857
5 200842
6 200940
7 200938
8 201138
9 200834
10 201326
11 201023
12 200723
13 201022
14 201020
15 201219
16 201819
17 201618
18 201418
19 202218
20 201016

About Daniel Nagaj

Daniel Nagaj is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics, Computational Theory and Mathematics, Condensed Matter Physics and Hardware and Architecture, having authored 28 papers that have together received 765 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (25 papers), Quantum Information and Cryptography (15 papers), Quantum many-body systems (7 papers), Quantum and electron transport phenomena (7 papers), Quantum Mechanics and Applications (6 papers), Quantum-Dot Cellular Automata (5 papers), Physics of Superconductivity and Magnetism (3 papers) and Machine Learning and Algorithms (3 papers). The work is most often cited by research in Artificial Intelligence (603 citations), Atomic and Molecular Physics, and Optics (466 citations), Computational Mathematics (9 citations), Computational Theory and Mathematics (139 citations) and Condensed Matter Physics (74 citations). Daniel Nagaj has collaborated with scholars based in Slovakia, United States and Czechia. Frequent co-authors include Paweł Wocjan, Mária Kieferová, Rolando D. Somma, Edward Farhi, Peter W. Shor, Jeffrey Goldstone, Ramis Movassagh, Jens Eisert, Vladimír Bužek and Dominik Hangleiter. Their work appears in journals such as Physical Review A, Quantum Information and Computation, Physical Review Letters, Science Advances and SIAM Journal on Computing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact